A novel hybrid invasive weed optimization algorithm for pattern synthesis of array antennas

2014 ◽  
Vol 25 (2) ◽  
pp. 154-163 ◽  
Author(s):  
Yan Liu ◽  
Yong-Chang Jiao ◽  
Ya-Ming Zhang
Keyword(s):  
Optimization Algorithm ◽  
Invasive Weed Optimization ◽  
Pattern Synthesis ◽  
Invasive Weed ◽  
Array Antennas

scholarly journals Thinning of Concentric Circular Antenna Arrays Using Improved Binary Invasive Weed Optimization Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Huaning Wu ◽  
Chao Liu ◽  
Xu Xie
Keyword(s):  
Antenna Arrays ◽  
Optimization Algorithm ◽  
Optimization Technique ◽  
Side Lobe Level ◽  
Circular Array ◽  
Invasive Weed Optimization ◽  
Pattern Synthesis ◽  
Invasive Weed ◽  
Circular Arrays ◽  
Concentric Circular Arrays

This study presents a novel optimization algorithm based on invasive weed optimization (IWO) for reduction of the maximum side lobe level (SLL) with specific half power beam width (HPBW) of thinned large multiple concentric circular arrays of uniformly excited isotropic elements. IWO is a powerful optimization technique for many continuous problems. But, for discrete problems, it does not work well. In this paper, the authors propose an improved binary IWO (IBIWO) for pattern synthesis of thinned circular array. The thinning percentage of the array is kept equal to or more than 50% and the HPBW is attempted to be equal to or less than that of a fully populated, uniformly excited, and half wavelength spaced concentric circular array of the same number of elements and rings. Simulation results are compared with previous published results of DE, MPSO, and BBO to verify the effectiveness of the proposed method for concentric circular arrays.

An Adaptive Invasive Weed Optimization Algorithm

2015 ◽  
Vol 29 (02) ◽  
pp. 1559004 ◽  
Author(s):  
Shuo Peng ◽  
A.-J. Ouyang ◽  
Jeff Jun Zhang
Keyword(s):  
Optimization Algorithm ◽  
Initial Step ◽  
Local Extremum ◽  
Invasive Weed Optimization ◽  
Step Size ◽  
Invasive Weed ◽  
Adaptive Step Size ◽  
Initial Step Size ◽  
Adaptive Step ◽  
Optimization Search

With regards to the low search accuracy of the basic invasive weed optimization algorithm which is easy to get into local extremum, this paper proposes an adaptive invasive weed optimization (AIWO) algorithm. The algorithm sets the initial step size and the final step size as the adaptive step size to guide the global search of the algorithm, and it is applied to 20 famous benchmark functions for a test, the results of which show that the AIWO algorithm owns better global optimization search capacity, faster convergence speed and higher computation accuracy compared with other advanced algorithms.

Sign in / Sign up

Export Citation Format

Share Document